Bare earth digital elevation model extraction for three-dimensional registration from topographical points

ABSTRACT

A method ( 300 ) for extracting a digital elevation model from a plurality of raw topographical points representing a plurality of frames representing a plurality of perspectives of a multi-dimensional object comprising a surface and above-surface obstructions, comprises steps or acts of: finding the surface ( 304 ) by filtering out data points produced by the above-surface obstructions to provide a plurality of surface data points representing the surface; and filtering the surface data points ( 306 ) with a competitive filter to provide a multi-dimensional surface shell of digital elevation model data points. The above-described method can also be carried out by a specialized or programmable information processing system ( 200 ) or as a set of instructions in a computer-readable medium such as a CD ROM or DVD or the like.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application relates to technology similar to that discussed inconcurrently filed U.S. patent applications Ser. No. 10/892,047 entitled“METHOD AND SYSTEM FOR SIMULTANEOUSLY REGISTERING MULTI-DIMENSIONALTOPOGRAPHICAL POINTS”, Ser. No. 10/892,055 entitled “SYSTEM AND METHODFOR IMPROVING SIGNAL TO NOISE RATIO IN 3-D POINT DATA SCENES UNDER HEAVYOBSCURATION”, and Ser. No. 10/892,063 entitled “METHOD AND SYSTEM FOREFFICIENT VISUALIZATION METHOD FOR COMPARISON OF LADAR POINT DATA TODETAILED CAD MODELS OF TARGETS” which are assigned to the same assigneeas the present application and are incorporated by reference herein intheir entirety.

FIELD OF THE INVENTION

The invention disclosed broadly relates to the field of a digital signalprocessing of topographical data and more particularly relates to asystem and method for extraction of digital elevation (DEM) models froma set of topographical points.

BACKGROUND OF THE INVENTION

Systems for processing digital representations of images are commonlyused to process data representing surfaces such as DEMs. A DEM isdigital map of the elevation of an area on the earth. The data iscollected by any well-known means such as LADAR (imaging Laser RADAR),or by IFSAR (Interferometric Synthetic Aperture Radar) or the like. Inoperation, the LADAR instrument transmits light to a target. Thetransmitted light interacts with and is changed by the target. Some ofthis light is reflected or scattered back to the sensor of theinstrument where it is detected, stored, and analyzed. The change in theproperties of the light enables some property of the target to bedetermined. The time required for light to travel to the target and backto the LADAR instrument is used to determine the range to the target.IFSAR is used to ingest and process high-resolution elevation dataproduced through a technique called radar interferometry. As in the caseof LADAR, IFSAR produces data useful for extracting DEMs.

Digital elevation models may be represented as a height map through grayscale images wherein the pixel values are actually terrain elevationvalues. The pixels are also correlated to world space (longitude andlatitude), and each pixel represents some variable volume of that spacedepending on the purpose of the model and land area depicted.

Referring to FIG. 1 there is shown an example of an airborne LADARsystem 100. The system comprises a LADAR instrument 102 mounted on thebottom of an aircraft 104. Below the aircraft is an area comprising theground and a canopy formed by trees and other foliage obstructing theview of the ground (earth) from an aerial view. The LADAR instrument 102emits a plurality of laser light pulses which are directed toward theground. The LADAR instrument 102 comprises a sensor 103 that detects thereflections/scattering of the pulses. The LADAR instrument 102 providesdata including elevation versus position information from a singleimage. It should be noted however, that multiple frames of portions ofthe area from different perspectives are used to generate the image. Thetree canopy overlying the terrain results in significant obscuration oftargets (e.g. tank 106) under that tree canopy. The points received bythe sensor of instrument 102 from the ground and the target 106 are thussparse. Hence, a robust system for processing the points is required.Moreover, to be of the most tactical and strategic value, an image ofthe ground wherein the target 106 can be perceived easily must beavailable quickly.

Extraction of data points generated by LADAR to produce a DEM is known.However, such methods are computationally intensive, and where a largenumber of data points are processed, run-time applications can bedifficult or slow. Therefore, there is a need for more efficient methodsand systems for production of DEMs using topological data points.

SUMMARY OF THE INVENTION

The above-discussed and other shortcomings of the prior art areaddressed and overcome by the present invention which provides a methodfor extracting a digital elevation model from a plurality of rawtopographical points representing a plurality of perspectives of amulti-dimensional object. The method comprises steps or acts of: findinga surface of the object by filtering out data points produced byabove-surface obstructions to provide a plurality of surface data pointsrepresenting the surface; and filtering the surface data points with acompetitive filter to provide a multi-dimensional surface shell ofdigital elevation model data points. The above-described method can alsobe carried out by a specialized or programmable information processingsystem or as a set of instructions in a computer-readable medium such asa CD ROM or DVD or the like.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a depiction of an airborne LADAR instrument for processingimages of a tree-covered terrain concealing a target.

FIG. 2 is a high level block diagram showing an information processingsystem according to an embodiment of the invention.

FIG. 3 is flowchart of a method for extracting a bare earth digitalelevation model according to another embodiment of the invention.

DETAILED DESCRIPTION

Referring to FIG. 2, there is shown high level block diagram showing aninformation processing system 200 using an embodiment of the invention.The system 200 comprises a source 202 of topographical data points.These points are preferably a plurality of three-dimensional (3D)topographical point values provided by a LADAR instrument 102 asdiscussed with respect to FIG. 1.

Referring again to FIG. 2, the data source 202 creates, in aconventional manner, a plurality of frames (or volumes) comprisingpoints representing a complex multidimensional object such as theterrain shown in FIG. 1. In this embodiment, the object comprises a basesurface (e.g., the ground or earth) and a plurality of obstructions(e.g., tree tops) above the surface. Each frame comprises the pointscollected by the sensor 103 over a given period of time (an exposure) asthe aircraft 104 moves over the terrain. In the preferred embodiment,this time period is one-third of a second and, with current instruments,that exposure results in collection of hundreds of thousands of pointsby the LADAR sensor 103. Each point is defined by a set ofthree-dimensional coordinates (x, y, z).

One way that the present system 200 improves on the performance of theprior art is, at least in part, by using only data points representingthe ground surface and a target 106 (if present) and not theobstructions at a height greater than a predetermined threshold abovethe ground. Using only the ground points greatly reduces the number ofpoints that are to be down-linked and processed and thus reduces thetime required to produce a model of the terrain.

The data provided by the LADAR instrument 102 may comprise an effectknown as ringing (or corona effect). Ringing is caused by scattering ofthe light produced by a target area that sometimes causes a false imageto appear. A ringing removal filter (circuitry or program logic) 204 isused for filtering the received 3D topographical points to remove theringing. Not all topographical data includes ringing. Therefore, thefiler 204 is not always required. The ringing is removed by ignoring alldata beyond a selected azimuth setting (for example), thus eliminatingany false images. The selection of the azimuth setting is governed bystatistical data or determined heuristically. In cases where the inputcomprises ringing, the use of the ringing removal filter 204 in system200 increases the signal to noise ratio at the output of the filter 204.

The output provided by the ringing noise removal filter 204 is receivedat a ground finder 206. The ground finder 206 is used for finding aground surface using the plurality of raw topographical points (e.g.,from the LADAR instrument 102) and their coordinates and providing aplurality of ground points representing a plurality of frames, in turnrepresenting patches of the ground surface and the target 106. Theground finder 206 finds the ground by extracting ground points from itsinput and filtering out points representing the obstructions such asthose from the top of the trees. As expected, the number of LADAR pulsesthat reach the ground through the trees and other foliage is muchsmaller than those emitted by the LADAR source (or emitter). Therefore,the points of light representing the ground (ground points) detected atthe LADAR sensor 103 is commensurately smaller than the total numberreceived from the totality of the terrain below the aircraft 104.

The ground finder 206 thus extracts a ground surface shell (a set ofpoints defining a three-dimensional surface) from the topographical dataprovided at the output of the ringing removal filter 204. The output ofthe ground finder 206 comprises a set of data representing the groundsurface that includes the target 106.

The ground finder 206 also operates to make sure that the ground iscontinuous so that there are no large changes in the topography. This isaccomplished by creating a two-dimensional (2D) grid for the groundsurface and determining the height of the ground at each grid component.Each grid component preferably represents a square part of the groundthat is one meter on each side. Once this data is collected for theentire grid, the ground finder 206 eliminates points that appear to beout of place or which are based on insufficient data. The decision onwhich points to eliminate is based on artifacts programmed into theground finder 206. The ground finder 206 is further programmed to ignoreany points higher than a predetermined height (e.g., the height of aperson, such as six feet) when calculating the contour of the groundsurface. The predetermined height is determined by rule-basedstatistics. That is done to eliminate any structures that are not likelyto be part of the ground. Thus, the output of the ground finder 206provides a more faithful representation of the actual ground surfacethan systems also using the treetop data.

The output of the ground finder 206 is provided to a competitive filter208. The competitive filter 208 is used to work on the ground surfacedata (ground points) provided by the ground finder 206. The groundpoints are filtered using the competitive filter 208 to obtain a 3Dshell of DEM points. The competitive filter 208 filters ground surfacedata not tied to geospatial coordinates such as the data collected bythe LADAR instrument 202. The filter 208 works by performing apolynomial fit of predetermined order for each frame of data points.This is done by determining which polynomial best represents the set ofpoints in the frame. One example is a first order polynomial (a tiltedplane) and the other is a numeric average (zero order). In the preferredembodiment, the average and the tilted plane (respectively, zero andfirst order polynomials) compete for the best fit in any given frame orvolume of points. Other embodiments may utilize higher orderpolynomials. A method for fitting polynomials in frames is discussed inU.S. patent application Ser. No. 09/827,305, the disclosure of which ishereby incorporated by reference in its entirety.

Thus, for every frame of points the filter 208 determines a tilted planethat fits the points in that frame. Each frame is a micro frame thatcovers a patch of ground constituting a small portion of the total areabeing processed. The output of the competitive filter 208 is a contourcomprising a plurality of (e.g., thirty) planes, one for each frameacquired. An optimal estimate of the ground surface allows forobscuration by the trees and foliage to produce an image of a partiallyobscured target. Once each frame is processed by the filter 208 theoutput is an unregistered DEM surface. In this embodiment the surface isa ground surface, however it should be appreciated that the method andsystem of the invention can be used on any surface of a target object.

The data produced by the competitive filter 208 DEM is not suitable forrendering an image that is useful to a user of the system 200. Toproduce a viewable image we must first complete a registration process.In the preferred embodiment the registration is performed by aniterative process performed by blocks 210 (a registration engine) and212 (a rigid transform engine). In this embodiment, to obtain a 3Drepresentation of the ground surface, several sets of data (frames) areautomatically pieced together to create an image of an entire targetarea or surface. Each set of data (or frame) is taken from a differentperspective providing a different view of the surface features.Registration determines the relative positions of each of the pointsrepresenting the surface as the sensor 103 moves over that surface. Thusdifferent views of the surface area are aligned with each other byperforming a translation and rotation of each frame to fit an adjacentframe or frames.

The first part of the registration process is to find in a second framethe closest point for each of a plurality of points in a first(adjacent) frame. Once the closest point is found, the points arealigned such that the frames make a good fit representing the registeredmodel or image. This is known as a pair wise process. Each iteration ofthe process produces a better fit and the process continues until anoptimum alignment is realized. This is accomplished by determining acomputation cost associate with each rotation and translation of eachframe to fit other frames. Using the information (matches betweenadjacent frames) collected in each iteration, subsequent iterationscorrect the alignment until an abort criterion is reached. Thiscriterion can be the completion of a number of iterations or theaccomplishment of a predetermined goal. In this embodiment, we performthe closest point search for each point in a first frame to locateclosest points in at least one other frame by entering observations fromeach iteration into a matrix and then solving the matrix at once so thatall transformations are performed substantially simultaneously (i.e., ann-wise process). An example of a matrix is found in J. A. Williams andM. Bennamoun, “Simultaneous Registration of Multiple Point Sets UsingOrthonormal Matrices” Proc. IEEE Int. Conf. on Acoustics, Speech andSignal Processing (ICASSP June 2000) at pp. 2199-2202.

In the preferred embodiment the iterative process is repeated several(e.g., five) times to determine an optimum rotation and translation forthe frames. We preferably use the algorithm presented in J. A. Williamsand M. Bennamoun, “Simultaneous Registration of Multiple Point SetsUsing Orthonormal Matrices” Proc. IEEE Int. Conf. on Acoustics, Speechand Signal Processing (ICASSP June 2000) at pp. 2199-2202, thedisclosure of which is hereby incorporated by reference.

The iterated transformations discussed above are performed at block 212.Each transformation is a rigid transformation. A transform is said to berigid if it preserves the distances between corresponding points.

The frame integrator block 214 performs an integration (or union) of theregistered volumes produced by block 212 and the result is cropped to asize and shape suitable for presentation and then it is visuallyexploited at block 216 to show the structure of the target. The resultis a 3D model that is displayed quickly. In the embodiment discussedherein a target such as the tank 106 hidden under the treetops as shownin FIG. 1 is depicted without the obscuring effect of the canopy oftrees over the tank 106.

As discussed above, the speed of the registration process is critical inmany applications such a locating a hidden target such as a tank 106 ina combat environment. One way to speed up the process is to improve thespeed of the search for corresponding points from frame to frame. Thiscan be accomplished by using any of several well-known k-D treealgorithms. Thus, the data points from each frame are mapped into a treestructure such that the entire set of points in an adjacent frame do nothave to be searched to find the closest point for a given point in afirst frame. An example of a k-D tree algorithm is found at the web sitelocated at http://www.rolemaker.dk/nonRoleMaker/uni/algogem/kdtree.htm.

Referring to FIG. 3, there is shown a flow chart illustrating asimplified method 300 for extraction of bare earth digital elevationmodel according to an embodiment of the invention. The method isperformed using a system such as the one described with respect to FIG.2. In step 302 the system receives a plurality of multi-dimensionalpoints representing a frame volume. In step 304 the system finds theground by isolating ground points from above-ground obstructions. Instep 306 the system filters the ground points to obtain amulti-dimensional shell of digital elevation model points. The result offiltering is a DEM representing the ground area beneath the obstructionsshown in FIG. 1. There are several possible applications for thisoutput.

Therefore, while there has been described what is presently consideredto be the preferred embodiment, it is understood by those skilled in theart that other modifications can be made within the spirit of theinvention.

1. A method for extracting a digital elevation model from a plurality ofraw topographical points representing a plurality of frames, each framerepresenting a perspective of a multi-dimensional object comprising asurface and above-surface obstructions, the method comprising: findingthe surface by filtering out data points representing the above-surfaceobstructions to provide a plurality of surface data points representingthe surface; and filtering the surface data points with a competitivefilter to provide a multi-dimensional surface shell of digital elevationmodel data points comprising a plurality of filtered frames.
 2. Themethod of claim 1, wherein the filtering with the competitive filtercomprises determining a plurality of tilted planes defining the surface.3. The system of claim 1, wherein the topographical points comprisecoordinates in three dimensions.
 4. The method of claim 1, furthercomprising registering the plurality of filtered frames.
 5. The methodof claim 4, further comprising using an iterative closest point processfor aligning data points in adjacent frames.
 6. The method of claim 4,further comprising integrating the plurality of filtered frames fordisplay thereof.
 7. The method of claim 1, further comprising performinga k-D tree search for each of a plurality of points in a first frame tofind a closest point in at least one adjacent frame.
 8. A system forextracting a bare earth digital elevation model from a plurality of rawtopographical points representing a multi-dimensional object comprisinga surface and above-surface obstructions, the system comprising: aground finder for finding a ground surface by receiving the plurality ofraw topographical Points representing a plurality of frames, each framerepresenting a portion of the surface and filtering ground points fromabove-ground obstruction points to provide a plurality of ground pointsrepresenting the ground surface; and a competitive filter for filteringthe ground points to obtain a multi-dimensional shell of digitalelevation model points.
 9. The system of claim 8, further comprisingregistration logic for registering the shell of digital elevation modelpoints.
 10. The system of claim 8, wherein the ground finder finds theground surface by processing ground points and clips every point above apredetermined threshold height.
 11. The system of claim 8, wherein themulti-dimensional points comprise coordinates in three-dimensions. 12.The system of claim 8 further comprising a ringing noise removal filterfor receiving the plurality of raw topographical points to remove anyringing effect in the raw topographical points and to provide a signalwith improved signal to noise ratio to the ground finder.
 13. The systemof claim 8 further comprising a LADAR sensor for receiving points oflight reflected or scattered by a subject surface and providing theplurality of topographical points.
 14. The system of claim 8 furthercomprising a LADAR source for emitting pulses of light to the surface.15. The system of claim 8 further comprising an IFSAR instrument forreceiving data points produced by a subject surface and providing theplurality of topographical points.
 16. A computer readable mediumcomprising program instructions for extracting a digital elevation modelfrom a plurality of raw topographical points representing a plurality offrames representing a plurality of perspectives of a multi-dimensionalobject comprising a surface and above-surface obstructions, the mediumcomprising instructions for: finding the surface by filtering out datapoints produced by the above-surface obstructions to provide a pluralityof surface data points representing the surface; and filtering thesurface data points with a competitive filter to provide amulti-dimensional surface shell of digital elevation model data pointscomprising a plurality of filtered frames.
 17. The medium of claim 16further comprising an instruction for registering the shell of digitalelevation model points.
 18. The medium of claim 16 further comprising aninstruction for using an iterative closest point algorithm.
 19. Themedium of claim 16 further comprising an instruction for using a fast KDTree search on adjacent collected pairs of surface shells findingrotation and translation parameters that are optimal for the currentiteration.